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Under the pressures of global climate change and human activities, the carrying capacity of water and soil resources in agricultural lands has decreased, and the traditional models of agricultural development are no longer sustainable. Land degradation, groundwater quality reduction and ecosystem instability are the consequences of agricultural development without considering sustainability indicators. This article aims to investigate the use of variable relationship analysis and Bayesian network methods to analyze and investigate the relationship between irrigation in agriculture and the sustainability of the groundwater ecosystem. Descriptive statistics of agriculture including cultivation pattern, time, precipitation, irrigation, and land slope were analyzed and combined with the simulated characteristics of groundwater including specific yield, hydraulic conductivity and hydrodynamic diffusion coefficients. Five crops of wheat, barley, paddy, alfalfa, and potato were studied to evaluate the effect of plants on the pattern of nitrate release due to irrigation and fertilization in agriculture. The results showed that managing the amount of fertilizer and the volume of irrigation can positively affect the nitrate distribution pattern in the groundwater even in a short period of time. HIGHLIGHTS The relationships between variables are used to build a logical model for analysis.; The quantity and quality of irrigation water is incorporated into the system for estimating the nitrate concentration in groundwater.;

Cultivated grasslands are an important part of grassland ecosystems and have been proven to be major carbon sinks, then playing an important role in the global carbon balance. The effect of cultivated grassland type (Medicago sativa, Triticum aestivum, Secale cereale, and Vicia villosa grasslands) on carbon flux (including net ecosystem CO2 exchange (NEE), ecosystem respiration (ER), and gross ecosystem productivity (GEP)) downstream of the Yellow River was studied via the static chamber technique and a portable photosynthetic system. Bare land was used as a control. The results showed that the four cultivated grassland types were mainly carbon sinks, and bare land was a carbon source. The cultivated grassland types significantly affected carbon flux. The average NEE and GEP of the grassland types were in the following order from high to low: Medicago sativa, Secale cereale, Triticum aestivum, and Vicia villosa grassland. Stepwise regression analysis showed that among all measured environmental factors, soil pH, soil bulk density (BD), soil organic carbon (SOC), and soil microbial carbon (MBC) were the main factors affecting CO2 flux. The combined influence of soil BD, SOC, and pH accounted for 77.6% of the variations in NEE, while soil BD, SOC, and MBC collectively explained 79.8% of changes in ER and 72.9% of the changes in GEP. This finding indicates that Medicago sativa grassland is a cultivated grassland with a high carbon sink level. The changes in carbon flux were dominated by the effects of soil physicochemical properties. [ABSTRACT FROM AUTHOR]

This research evaluated several methods to help reduce pivot ruts or wheel tracks on pivots. On-farm trials were established at nine site-years with corn (Zea mays L.), alfalfa (Medicago sativa L.) and wheat (Triticum aestivum L.) during 2020–2022 in Utah and Idaho. The eight-boom design (i.e., Advantage booms) had mostly positive crop responses but did not reduce wheel track depth. The part circle (PC) method provided much shallower tracks at one site, but it also lowered crop yield. At other sites there were minimal effects to yield and quality with the PC method, but the early-season, shallow wheel tracks did not usually last through the heaviest time of irrigating. The low energy precision application (LEPA) method was the most reliable method for maintaining crop yield and quality, while improving wheel tracks. The single boom method often maintained crop quality, but it also often reduced yield, and did not improve wheel tracks compared with the nontreated controls. The polyacrylamide had few effects on crop yield and quality, or wheel track depth. There was no approach in the study that maintained yield and reduced pivot track depth compared with no treatment in every scenario, but the LEPA method displayed the greatest potential for uniformly irrigating the area near the wheel track to maintain crop yield and quality, while minimizing water entering the track, to help reduce burdensome pivot ruts. Thus, LEPA may be one of the most effective sprinkler modifications for reducing pivot tracks and adequately irrigating the area around the track. This research evaluated how several sprinkler modifications and a soil conditioner help reduce pivot ruts or wheel tracks on pivot irrigation systems. On-farm research trials were established at six fields with corn, alfalfa, and wheat during 2020–2022 in Utah and Idaho. The eight-boom sprinkler modification had mostly positive crop responses but did not reduce wheel track depth. The part circle (PC) sprinkler method sometimes reduced wheel rut depth but came at the expense of lost crop production. The low energy precision application (LEPA) sprinkler method was the most reliable method for maintaining crop yield and quality, while improving wheel tracks. The single boom method often reduced yield and did not improve wheel tracks compared with the nontreated tracks. The polyacrylamide soil conditioner had few effects on crop yield and quality, or wheel track depth. There was no approach in the study that maintained yield and reduced pivot track depth compared with no treatment in every scenario, but the LEPA method displayed the greatest potential for uniformly irrigating the area near the wheel track and maintaining crop yield and quality. Thus, LEPA may be one of the most effective tools for reducing pivot tracks and adequately irrigating the area around the track. [ABSTRACT FROM AUTHOR]

We evaluated the impact of weather and fertilization treatments (Control, PK, NPK1, NPK2, and NPK3) on winter wheat grain yields in a long-term trial in Ivanovice, Czech Republic, established in 1956. A total of 15 seasons were evaluated. The mean, maximal, and minimal temperatures in Ivanovice have been significantly increasing since 1961, with annual increases of 0.04 °C, 0.03 °C, and 0.05 °C, respectively. Precipitation has been decreasing annually by −0.54 mm (trend is insignificant). Four significant correlations between weather and grain yield were recorded. There were positive correlations between mean (r = 0.7) and minimal (r = 0.5) temperatures in November and negative correlations between mean temperatures in May (r = −0.6) and June (r = −0.6). The combination of naturally fertile chernozem soil and a beneficial preceding crop (alfalfa) enables sustainable cultivation of wheat, even without mineral fertilizers. The application of mineral nitrogen (N) significantly increases wheat grain yield and yield stability. Without mineral N or with high doses of mineral N, yield stability decreases. According to two response models (quadratic and quadratic-plateau), a reasonable dose of fertilizer is 107 kg ha−1 N for modern wheat varieties, corresponding to a yield of 8.1 t ha−1. [ABSTRACT FROM AUTHOR]

Local agrobiodiversity in remote areas such as the Moroccan High Atlas is poorly studied, despite being of great importance for the sustainability and resilience of mountainous populations. This includes important species such as wheat (Triticum spp.), barley (Hordeum vulgare), fava beans (Vicia faba), peas (Pisum sativum), and alfalfa (Medicago sativa). This study aimed to better understand varietal naming by farmers and the traits they use for assessing the current diversity of the five species, in 22 locations, distributed across three hubs of the High Atlas. The data were provided by 282 Amazigh informants during focus-group discussions, household surveys, and market surveys, with the support of the Diversity Assessment Tool for Agrobiodiversity and Resilience (DATAR). The use of local terminology for variety names and systematically collected morphological, ecological, and use descriptors appears to be a valuable way to assess local intraspecific diversity, and further comparisons with genomic results are recommended. Furthermore, the results also indicate low diversity at the household level, which contrasts with the greater diversity at the community level. Larger areas are still planted with landraces compared to areas planted with modern varieties, although the levels of richness (number) of both landraces and modern varieties are equivalent overall. Many factors influence this diversity: the biophysical characteristics of the sites, the socio-economic and management practices of farmers, and the availability of varietal diversity and of modern varieties or landraces. Although selection processes have reduced the local diversity available for economically important crops, we found that farmers still rely greatly on landraces, which present traits and variability that allow them to adapt to local conditions. [ABSTRACT FROM AUTHOR]

This review describes the role of silicon (Si) in plants. Methods of silicon determination and speciation are also reported. The mechanisms of Si uptake by plants, silicon fractions in the soil, and the participation of flora and fauna in the Si cycle in terrestrial ecosystems have been overviewed. Plants of Fabaceae (especially Pisum sativum L. and Medicago sativa L.) and Poaceae (particularly Triticum aestivum L.) families with different Si accumulation capabilities were taken into consideration to describe the role of Si in the alleviation of the negative effects of biotic and abiotic stresses. The article focuses on sample preparation, which includes extraction methods and analytical techniques. The methods of isolation and the characterization of the Si-based biologically active compounds from plants have been overviewed. The antimicrobial properties and cytotoxic effects of known bioactive compounds obtained from pea, alfalfa, and wheat were also described. [ABSTRACT FROM AUTHOR]

Within the framework of a long-term experiment, established in 1955, we evaluated the development and effects of weather and mineral fertilization (Control, NPK1, NPK2, NPK3, NPK4) on the yield and stability of winter wheat following alfalfa. In total, 19 seasons were analysed. The weather changed considerably at the experimental site. Significant increases in minimal, mean, and maximal temperatures were dated to the period 1987–1988, while precipitation remained the same to this day (insignificantly increasing trend by 0.5 mm per annum). Rising temperatures in November, May, and July positively affected wheat grain yield, especially in treatments with higher N doses. No relationship between yield and precipitation was recorded. Highest inter-annual yield variability was recorded in Control and NPK4 treatments. Although minerally fertilized treatments provided slightly higher yields, the difference between Control and NPK treatments was insignificant. According to the linear-plateau response model, the recommended dose of 44 kg ha−1 N corresponds with yield of 7.4 t ha−1, while Control provides an average yield of 6.8 t ha−1. The application of higher doses did not lead to significant grain yield increase. Alfalfa as a preceding crop reduces the need of N fertilization and contributes to sustainable conventional agriculture, however, its share in crop rotations is decreasing both in the Czech Republic and in Europe. [ABSTRACT FROM AUTHOR]

The PLATZ family is a novel class of plant-specific zinc finger transcription factors with important roles in plant growth and development and abiotic stress responses. PLATZ members have been identified in many plants, including Oryza sativa, Zea mays, Triticum aestivum, Fagopyrum tataricum, and Arabidopsis thaliana; however, due to the complexity of the alfalfa reference genome, the members of the PLATZ gene family in alfalfa (Medicago sativa L.) have not been systematically identified and analyzed. In this study, 55 Medicago sativa PLATZ genes (MsPLATZs) were identified in the alfalfa "Xinjiangdaye" reference genome. Basic bioinformatic analysis was performed, including the characterization of sequence lengths, protein molecular weights, genomic positions, and conserved motifs. Expression analysis reveals that 7 MsPLATZs are tissue-specifically expressed, and 10 MsPLATZs are expressed in all examined tissues. The transcriptomic expression of these genes is obvious, indicating that these MsPLATZs have different functions in the growth and development of alfalfa. Based on transcriptome data analysis and real-time quantitative PCR (RT-qPCR), we identified 22, 22, and 21 MsPLATZ genes that responded to salt, cold, and drought stress, respectively, with 20 MsPLATZs responding to all three stresses. This study lays a foundation for further exploring the functions of MsPLATZs, and provides ideas for the improvement of alfalfa varieties and germplasm innovation. [ABSTRACT FROM AUTHOR]

Several studies have shown the potential of using mycorrhizal fungi in increasing the plant yield by simultaneously reducing damages caused by pathogens. Plant parasitic nematodes (PPNs) are among the most feared pathogens for crops. This study aimed to evaluate the effects of Funneliformis mosseae as a mycorrhizal fungus on the population abundance of three world widespread species of nematodes from the family Criconematidae: Mesocriconema xenoplax, Mesocriconema antipolitanum, and Criconemides informis. Pure and highly abundant populations of each species were collected from Urmia city in Northwestern Iran, after the identification morphological and morphometric characteristics. The experiments were carried out in greenhouse conditions on three different rhizospheres of alfalfa, sugar beet, and wheat. After five months, the final population of nematodes and fungus, and the root surface on host plants inoculated and non-inoculated with the fungus F. mosseae, were evaluated. The results showed that the population of nematodes was increased in the presence of the fungus. It could be assumed that the extension of the host surface level of roots by the fungus resulted in more feeding sites for nematode activity and, consequently, higher population densities. In this study, the fungus did not seem to play a suitable role in controlling ectoparasitic nematode growth. However, since there are still many open questions about mycorrhizal fungi's role in agriculture, more research should be conducted. [ABSTRACT FROM AUTHOR]

Cropping systems are one of the most important living components affecting the surface soil spatial variability. Composite disturbed and undisturbed soils were collected (intersections of the grid system, 50 x 50 m) at 0-20 and 20-40 cm depths under maize (Zea mays), wheat (Triticum aestivum), and alfalfa (Medicago sativa L.) cropping systems from the farmer’s field, in the Igdir Plain, eastern Turkey. Soil spatial variability was based on clay, silt, and sand, calcium carbonate (CaCO3) and organic matter, the pH, electrical conductivity, bulk density, aggregate stability and penetration resistance of the soil were determined. The data was analysed using both statistical and geostatistical approaches and suggested that the spatial distribution model and spatial dependence level varied significantly within the farm soils. Exponential, Gaussian, and spherical semivariogram models were found to be the best models to explain the spatial structure of the soil properties. Clay and sand, electrical conductivity, soil organic matter, bulk density, aggregate stability, and penetration resistance were found to be significantly different between the soil depths. The soil property ranges of the variogram were between 58.5 and 305.9 m and showed a moderate to strong spatial dependence. The development of spatial distribution maps for the soil variables analysed provided for a comparison to be made between the various soil properties and raises the possibility of understanding heterogeneity within the farm in the form of a regional representation. It may be concluded that these maps will assist in determining site-specific soil use and identifying the impact of soil management. [ABSTRACT FROM AUTHOR]

Simple Summary: A common nutritional strategy to reduce heat stress on dairy cows is to provide a more slowly degradable starch source that reduces the amount of heat generated during digestion. The aim of this experiment was to investigate the responses of late lactation dairy cows to cereal grain-based diets in a short-term heat challenge. Cows were offered a diet of alfalfa hay supplemented with either wheat grain (fast rumen degradable) or corn grain (slow rumen degradable). Individual cow measurements of feed intake, milk yield and composition, respiration rate, and body temperature were taken daily before, during and after a 4-day heat challenge, during which the cows were in individual controlled-climate chambers and exposed to air temperature up to 33 °C with 50% relative humidity. While exposed to the heat challenge during late lactation, cows that were offered corn grain had greater feed intake and tended to produce more energy-corrected milk but had lower respiration rates and similar body temperature to the cows offered wheat grain. The economic impact of feeding corn in place of wheat grain needs to be assessed before any comparative value of feeding corn grain or wheat grain can be determined. Cereal grains that differ in the rate and extent of ruminal fermentation differ in heat increment and may be used to improve thermoregulation during heat stress. This experiment investigated the responses of dairy cows in late lactation to a heat challenge when offered wheat-grain or corn-grain. Eighteen lactating cows, 220 ± 94 (mean ± standard deviation) days in milk, 3.7 ± 0.17 years of age and 558 ± 37 kg bodyweight, were allocated treatments containing 6 kg dry matter (DM)/day of wheat grain or 6 kg DM/day corn grain (9 per treatment) plus 14 kg DM/day of alfalfa hay. Measurements were made during a 7-day pre-challenge period at ambient conditions in individual stalls, during a 4-day heat challenge (temperature humidity index of 74 to 84) in individual controlled-climate chambers, then during a 7-day recovery period at ambient conditions in individual stalls. During the heat challenge, cows offered corn had lower respiration rates (p = 0.017) and greater feed intake (p = 0.021) but energy-corrected milk (p = 0.097) was not different to that of cows offered wheat. Feeding corn grain to dairy cows during a heat challenge reduced some of the negative impacts of heat stress, enabling the cows to consume more forage compared with supplementing with wheat grain. [ABSTRACT FROM AUTHOR]

Wheat, alfalfa, and radish sprouts are well-renowned for their high nutritional content. However, their optimal imbibition and germination durations are rarely considered in the literature. In this study, reduced imbibition times of 3 h, 10 h, and 4 h were demonstrated for the wheat, alfalfa, and radish seeds, respectively. The evolution of their crude fat, proteins, polyphenols, antioxidant activity, and vitamins were investigated over 7 days of germination. The crude fat and protein loads of these sprouts slightly varied during germination, whereas the phenolic compounds and antioxidant activity maxed out at day 7, 5, and 6 for the wheat, alfalfa, and radish sprouts, respectively, with significant levels of catechin. The vitamins highly increased, showing noteworthy yet different peaks of growth depending on the seed and the vitamin analyzed. Interestingly, alfalfa and radish sprouts, taken at their optimal germination day, would decidedly contribute to meet our Recommended Daily Allowances (RDAs) of vitamins E, A, and B6. Overall, for a greater nutritional content and a potential use of these sprouts as nutraceutical ingredients, our results suggested to leave the wheat, alfalfa, and radish seeds to germinate only over 7, 4, and 6 days, respectively, after which their nutritional quality tended to decrease. [ABSTRACT FROM AUTHOR]

This study was conducted to investigate the effects of vegetation type (Alfalfa and Wheat) and slope (5% and 20%) on runoff and drainage pollution in clay loam soil. Sampled soils were repacked in the box with one soil drainage outlet and one surface flow outlet and were cultivated by wheat or alfalfa. A solution containing 0.05 M KCl was poured quickly and uniformly, over the surface of each box, after plant growth. Simulated rainfall was applied to the soil box with the intensity of a constant rate of 64 mm h-1 for 2 hours immediately. Then the concentration of Cl- and K+ were measured in the collected samples of runoff and the drainage outlet. Results showed that the measured concentration of K+ was lower than the Cl- concentration as a result of its absorbable property. The breakthrough curves (BTCs) of Cl- and K+ showed that slope and vegetation type affected the transport of Cl- and K+. The peak of the BTCs for Cl- and K+ in runoff ranked in the order of wheat and 20% slope> alfalfa and 20% slope> wheat and 5% slope> alfalfa and 5% slope, and in the drainage changed to alfalfa and 5% slope> wheat and 5% slope> alfalfa and 20% slope> wheat and 20% slope. For each slope, the intensive vegetation cover of alfalfa than wheat considerably reduces Cl- or K+ pollution in runoff; whereas drainage development of larger and deeper root systems was the cause of higher leached concentrations for both tracers. Based on our research changes in soil surface vegetation cover from wheat to alfalfa are suggested in slope land to prevent surface water pollution; although other factors such as the climate, soil texture, and structure should also be considered. [ABSTRACT FROM AUTHOR]

Within Mediterranean cropping systems, legume forage crops that last up to 6 years or more (e.g., alfalfa) are replaced with cereal crops (e.g., wheat). The change from forage to cereal crops has negative climate and environmental impacts that must be addressed with mitigation actions. This study evaluated the synergies and tradeoffs between the ecosystem services provided by three management systems after forage legume. A field trial was set up from October 2017 to September 2019 on a 6-year-old alfalfa field subjected to the following management systems: (i) alfalfa termination followed by wheat for 2 years (WW, control); (ii) alfalfa termination followed by single amendment with 60 Mg ha−1 recalcitrant biochar and then by wheat for 2 years (WWB60); and (iii) extension of alfalfa for 2 years (AEXT). A range of regulating, supporting, and provisioning ecosystem services were assessed during the 2018 and 2019 cropping seasons. The results highlight that WWB60 can guarantee carbon sequestration without causing tradeoffs with other services, while AEXT can enhance soil conservation while not increasing soil greenhouse gas emissions. Future policies should support the WWB60 system if the goal is to increase the supporting services. Conversely, the AEXT system should be used if the goal is to increase the regulating and provisioning services. [ABSTRACT FROM AUTHOR]

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The research presented in this paper was carried out during three years of study (2018-2020) and aimed at studying soil erosion and losses of humus and major macroelements (nitrogen, phosphorus, potassium) based on the precipitation regime that produced runoff on the slope. The research was carried out on a stagnic vertic preluvosoil with a slope of 4%, with a moderate acid reaction and a medium supply of nitrogen and potassium, and weak supply of phosphorus from Balota de Sus area, Dolj County, comprising 3 crops practiced in the area: wheat, corn, alfalfa compared to the field black (uncultivated) and spontaneous vegetation (natural). Following the researches, it was found that the most significant runoff on the slope was recorded in black fallow 471.98 mc/ha and corn 252.62 mc/ha, and the lowest were recorded in wheat 183.43 mc/ha and alfalfa 118.87 mc/ha (25.14% compared to the black fallow). Soil erosion, or soil losses, recorded high values also in the case of corn cultivation 6.84 t/ha (39.42%) and in the case of black fallow 17.35 t/ha (100%). The humus in the soil was lost in the largest quantities also in the corn crop 198.19 kg/ha (40.56%) and black fallow 488.58 kg/ha (100%) and in quite small quantities in the case of alfalfa 89.20 kg/ha (18.25 %). Nutrients in the soil have been lost, both by runoff water on sloping soil and by eroded soil, with higher amounts lost through eroded soil. [ABSTRACT FROM AUTHOR]

Several studies have shown the potential of using mycorrhizal fungi in increasing the plant yield by simultaneously reducing damages caused by pathogens. Plant parasitic nematodes (PPNs) are among the most feared pathogens for crops. This study aimed to evaluate the effects of Funneliformis mosseae as a mycorrhizal fungus on the population abundance of three world widespread species of nematodes from the family Criconematidae: Mesocriconema xenoplax, Mesocriconema antipolitanum, and Criconemides informis. Pure and highly abundant populations of each species were collected from Urmia city in Northwestern Iran, after the identification morphological and morphometric characteristics. The experiments were carried out in greenhouse conditions on three different rhizospheres of alfalfa, sugar beet, and wheat. After five months, the final population of nematodes and fungus, and the root surface on host plants inoculated and non-inoculated with the fungus F. mosseae, were evaluated. The results showed that the population of nematodes was increased in the presence of the fungus. It could be assumed that the extension of the host surface level of roots by the fungus resulted in more feeding sites for nematode activity and, consequently, higher population densities. In this study, the fungus did not seem to play a suitable role in controlling ectoparasitic nematode growth. However, since there are still many open questions about mycorrhizal fungi’s role in agriculture, more research should be conducted.

Purpose: Extracellular deoxyribonucleases (exDNases) from microbial origin contribute substantially to the restriction of extracellular DNA (exDNA) in the soil. Hence, it is imperative to understand the diversity of bacterial species capable of performing this important soil function and how crop species influence their dynamics in the soil. The present study investigates the occurrence of DNase-producing bacteria (DPB) in leachate samples obtained from soils in which the crop species of alfalfa (Medicago sativa L.), canola (Brassica napus L.), soybean (Glycine max [L.] Merr.) and wheat (Triticum aestivum L.) were raised in a growth room. Methods: Selective media containing methyl green indicator was used to screen for DPB from leachate samples, whereas the 16S rRNA sequence analysis was employed to identify the isolates. Results: The proportion of culturable DPB ranged between 5.72 and 40.01%; however, we did observe specific crop effects that shifted throughout the growing period. In general, higher proportions of exDNase producers were observed when the soils had lower nutrient levels. On using the 16S rRNA to classify the DPB isolates, most isolates were found to be members of the Bacillus genera, while other groups included Chryseobacterium, Fictibacillus, Flavobacterium, Microbacterium, Nubsella, Pseudomonas, Psychrobacillus, Rheinheimera, Serratia and Stenotrophomonas. Five candidate exDNase/nuclease-encoding proteins were also identified from Bacillus mycoides genomes using online databases. Conclusion: Results from this study showed that crop species, growth stage and soil properties were important factors shaping the populations of DPB in leachate samples; however, soil properties seemed to have a greater influence on the trends observed on these bacterial populations. It may be possible to target soil indigenous bacteria that produce exDNases through management to decrease potential unintended effects of transgenes originating from genetically modified organisms (GMOs) or other introduced nucleic acid sequences in the environment. [ABSTRACT FROM AUTHOR]

The assessment of soil suitability for sustainable intensive agriculture is important for the selection of land suitable for agricultural production with the least economic and environmental costs. This study was directed to evaluate agricultural soil suitability in the south of Hail province, Saudi Arabia to suggest alternative crops of alfalfa using the Agricultural Land Evaluation System for arid regions (ALES-Arid) model and Geographic Information System (GIS). The study area covers about 77558 ha and 111 soil samples were collected from 37 profiles and 37 groundwater samples were analyzed for physical, chemical and fertility properties. To evaluate land suitability for selected crops, the FAO guideline was used and also to analyze and map soils within the study area, the GIS was employed. The main research goals were to characterize the soil and water resources of the study area, in order to plan the best alternative crops of alfalfa using land evaluation facilities for different purposes (capability and suitability). The results indicated that the soils of the area are characterized by sandy loam texture, low fertility, low total carbonate and most of the area have moderate to high salinity soil. Capability classes of the area are C3 and C4 which covers about 89.19% and 10.81% of the total area, respectively. The most fertile classes were situated in C2 and C3 which covers 37.84 and 40.54% of the area with phosphorus and potassium limitation. The land suitability results show that 99.68, 97.18 and 85.37% of the area is classified as S1 (highly suitable) for wheat, barley and alfalfa, respectively; while 98.91% of the area is classified as S3 (marginally suitable) for maize. From the obtained data, growers are advised to cultivate barley or wheat in winter and maize in summer instead of alfalfa, in order to save irrigation water. This is also because the expected productivity of either wheat or barley is high. It is important for decision makers to determine the best way of using land for agricultural purposes, since it serves as a decision and planning support. [ABSTRACT FROM AUTHOR]

Agricultural production systems in New Mexico (NM) are under increased pressure due to climate change, drought, increased temperature, and variable precipitation, which can affect crop yields, feeds, and livestock grazing. Developing more sustainable production systems requires long-term measurements and assessment of climate change impacts on yields, especially over such a vulnerable region. Providing accurate yield predictions plays a key role in addressing a critical sustainability gap. The goal of this study is the development of effective crop yield predictions to allow for a better-informed cropland management and future production potential, and to develop climate-smart adaptation strategies for increased food security. The objectives were to (1) identify the most important climate variables that significantly influence and can be used to effectively predict yield, (2) evaluate the advantage of using remotely sensed data alone and in combination with climate variables for yield prediction, and (3) determine the significance of using short compared to long historical data records for yield prediction. This study focused on yield prediction for corn, sorghum, alfalfa, and wheat using climate and remotely sensed data for the 1920–2019 period. The results indicated that the use of normalized difference vegetation index (NDVI) alone is less accurate in predicting crop yields. The combination of climate and NDVI variables provided better predictions compared to the use of NDVI only to predict wheat, sorghum, and corn yields. However, the use of a climate only model performed better in predicting alfalfa yield. Yield predictions can be more accurate with the use of shorter data periods that are based on region-specific trends. The identification of the most important climate variables and accurate yield prediction pertaining to New Mexico’s agricultural systems can aid the state in developing climate change mitigation and adaptation strategies to enhance the sustainability of these systems.

The leaf area index (LAI) is a key biophysical variable for agroecosystem monitoring, as well as a relevant state variable in crop modelling. For this reason, temporal and spatial determination of LAI are required to improve the understanding of several land surface processes related to vegetation dynamics and crop growth. Despite the large number of retrieved LAI products and the efforts to develop new and updated algorithms for LAI estimation, the available products are not yet capable of capturing site-specific variability, as requested in many agricultural applications. The objective of this study was to evaluate the potential of non-parametric approaches for multi-temporal LAI retrieval by Sentinel-2 multispectral data, in comparison with a VI-based parametric approach. For this purpose, we built a large database combining a multispectral satellite data set and ground LAI measurements collected over two growing seasons (2018 and 2019), including three crops (i.e., winter wheat, maize, and alfalfa) characterized by different growing cycles and canopy structures, and considering different agronomic conditions (i.e., at three farms in three different sites). The accuracy of parametric and non-parametric methods for LAI estimation was assessed by cross-validation (CV) at both the pixel and field levels over mixed-crop (MC) and crop-specific (CS) data sets. Overall, the non-parametric approach showed a higher accuracy of prediction at pixel level than parametric methods, and it was also observed that Gaussian Process Regression (GPR) did not provide any significant difference (p-value > 0.05) between the predicted values of LAI in the MC and CS data sets, regardless of the crop. Indeed, GPR at the field level showed a cross-validated coefficient of determination (R2CV) higher than 0.80 for all three crops.

Due to the quantity and quality limitations of available water resources, the measurement and analysis of water and economic productivity indices in various irrigation systems (including surface and pressurized systems) has a great importance. The objective of this study was to compare water and economic productivity of pressurized and surface irrigation systems. For this purpose, the data of irrigation systems as well as crop yield in Qazvin Plain in 2011 were used. The required data were collected using the survey in the studied fields, questionnaires, the design report of irrigation systems and Qazvin Agriculture Organization. The results showed that the irrigation water productivity for barley, alfalfa, maize and wheat was 0.75 to 2.5, 0.2 to 1.76, 0.3 to 2.78 and 0.61 to 2.2 kg/m3, respectively, in sprinkler irrigation systems. In surface irrigation system, the water productivity for barley, alfalfa, maize and wheat was 0.43 to 1.42, 0.12 to 1.64, 0.22 to 1.58 and 0.43 to 1.25 kg/m3, respectively. The minimum and maximum amounts of economic productivity of surface irrigation systems in Rials/m3 were 1387 and 4617 for barely, 382 and 5050 for alfalfa, 905 and 6474 for maize and 1447 and 4159 for wheat. The minimum and maximum values of economic productivity of sprinkler irrigation systems in Rial/m3 were 2442 and 8126 for barley, 673 and 5420 for alfalfa, 1283 and 11395 for maize and 2016 and 7319 for wheat.

Landscape complexity influences soybean aphid suppression by generalist predators in North America, but the role of adjacent habitats as sources of these predators has not been studied directly. We quantified movement of aphidophagous predators between soybean and five adjacent habitats common in Manitoba using bi-directional Malaise traps. To test the contribution of predators from neighboring habitats to soybean aphid suppression, we performed experimental manipulations in adjacent soybean and alfalfa fields and monitored the movement of sevenspotted lady beetles, Coccinella septempunctata, using mark-release-recapture experiments. The identity of adjacent habitats affected the net movement of predators into soybean. The most abundant predators were hover flies (Diptera: Syrphidae), moving from woodlands to soybean. Similar (but non-significant) trends were found for lady beetles, minute pirate bugs, and green and brown lacewings. There was also a net movement of hover flies and green lacewings from soybean to canola. Lady beetles showed higher bidirectional movement in alfalfa and wheat borders than in woodland and canola borders in a high lady beetle abundance year. Soybean aphid populations in predator exclusion cages were 21- to 122- fold higher than populations exposed to predators, both in alfalfa and soybean fields. Aerial predators provide similar levels of aphid suppression as aerial and epigeal predators combined. Mark-release-recapture experiments showed high dispersal of C. septempunctata between soybean and alfalfa, with a net movement towards alfalfa, probably due to the lack of aphids in soybean. These results demonstrate that predator assemblages from both soybeans and alfalfa can suppress soybean aphids. Our findings indicate that the type of adjacent habitat and predator identity affect the directionality of predator movement into soybean. This study suggests that information on predator movement can be used to design the distribution of crops and natural habitats in agricultural landscapes that maximize pest control services. [ABSTRACT FROM AUTHOR]

Knowledge of baseline water use for irrigated crops in the U.S. Southwest is important for understanding how much water is consumed under normal farm management and to help manage scarce resources. Remote sensing of evapotranspiration (ET) is an effective way to gain that knowledge: multispectral data can provide synoptic and time-repetitive estimates of crop-specific water use, and could be especially useful for this arid region because of dominantly clear skies and minimal precipitation. Although multiple remote sensing ET approaches have been developed and tested, there is not consensus on which of them should be preferred because there are still few intercomparison studies within this environment. To help build the experience needed to gain consensus, a remote sensing study using three ET models was conducted over the Central Arizona Irrigation and Drainage District (CAIDD). Aggregated ET was assessed for 137 wheat plots (winter/spring crop), 183 cotton plots (summer crop), and 225 alfalfa plots (year-round). The employed models were the Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC), the Two Source Energy Balance (TSEB), and Vegetation Index ET for the US Southwest (VISW). Remote sensing data were principally Landsat 5, supplemented by Landsat 7, MODIS Terra, MODIS Aqua, and ASTER. Using district-wide model averages, seasonal use (excluding surface evaporation) was 742 mm for wheat, 983 mm for cotton, and 1427 mm for alfalfa. All three models produced similar daily ET for wheat, with 6⁻8 mm/day mid-season. Model estimates diverged for cotton and alfalfa sites. Considering ET over cotton, TSEB estimates were 9.5 mm/day, METRIC 6 mm/day, and VISW 8 mm/day. For alfalfa, the ET values from TSEB were 8.0 mm/day, METRIC 5 mm/day, and VISW 6 mm/day. Lack of local validation information unfortunately made it impossible to rank model performance. However, by averaging results from all of them, ET model outliers could be identified. They ranged from −10% to +18%, values that represent expected ET modeling discrepancies. Relative to the model average, standardized ET-estimators—potential ET (ET ∘ ), FAO-56 ET, and USDA-SW gravimetric-ET— showed still greater deviations, up to 35% of annual crop water use for summer and year-round crops, suggesting that remote sensing of actual ET could lead to significantly improved estimates of crop water use. Results from this study highlight the need for conducting multi-model experiments during summer-months over sites with independent ground validation.

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The effect of cropping system on the distribution of organic carbon (OC) and nitrogen (N) in soil aggregates has not been well addressed, which is important for understanding the sequestration of OC and N in agricultural soils. We analyzed the distribution of OC and N associated with soil aggregates in three unfertilized cropping systems in a 27-year field experiment: continuously cropped alfalfa, continuously cropped wheat and a legume-grain rotation. The objectives were to understand the effect of cropping system on the distribution of OC and N in aggregates and to examine the relationships between the changes in OC and N stocks in total soils and in aggregates. The cropping systems increased the stocks of OC and N in total soils (0–40 cm) at mean rates of 15.6 g OC m-2 yr-1 and 1.2 g N m-2 yr-1 relative to a fallow control. The continuous cropping of alfalfa produced the largest increases at the 0–20 cm depth. The OC and N stocks in total soils were significantly correlated with the changes in the >0.053 mm aggregates. 27-year of cropping increased OC stocks in the >0.053 mm size class of aggregates and N stocks in the >0.25 mm size class but decreased OC stocks in the <0.053 mm size class and N stocks in the <0.25 mm size class. The increases in OC and N stocks in these aggregates accounted for 99.5 and 98.7% of the total increases, respectively, in the continuous alfalfa system. The increases in the OC and N stocks associated with the >0.25 mm aggregate size class accounted for more than 97% of the total increases in the continuous wheat and the legume-grain rotation systems. These results suggested that long-term cropping has the potential to sequester OC and N in soils and that the increases in soil OC and N stocks were mainly due to increases associated with aggregates >0.053 mm. [ABSTRACT FROM AUTHOR]

The increasing demand for high-quality animal protein calls for parts of cereal cropping systems converting to forage or forage-livestock integrated systems. This study aimed at evaluating potential environmental impacts of this transition at the farm level on the Loess Plateau of China through a life cycle assessment (LCA) approach. Four dominating crops: alfalfa, wheat, grain maize and silage maize were studied based on the ten impact categories. Based on standard unit land area (1 ha) and timestamp (2018–2020) settings, alfalfa production indicated the lowest environmental impact in nine categories compared to other crops, while wheat indicated better performance in seven of ten impact categories than other crops except alfalfa. With respect to the environmental loads of grain maize and silage maize production, both systems were very comparable. Because of the common adoption of open-land burning of straws (mainly for fuel and winter heating) in the local region, the respiratory inorganics and photochemical oxidant formation potential impact of alfalfa and silage maize per hectare produced is much lower than those of wheat and grain maize. Great differences in environmental impacts between the two types of cropping systems (cereal vs forage) indicate that transitioning from cereal to forage production should effectively reduce air pollution and enhance environmental sustainability on the Loess Plateau. Besides, uncertainty and variability of LCAs results were analyzed in this study. [Display omitted] • Environmental impacts of four types of cropping systems were compared by land unit. • Impact variability among farms was analyzed through 607 LCAs. • Performance of most impact categories was alfalfa>wheat>silage maize>grain maize. • Forage cropping systems incurred less air pollution than cereal systems. [ABSTRACT FROM AUTHOR]

Non-destructive biomass estimation of vegetation has been performed via remote sensing as well as physical measurements. An effective method for estimating biomass must have accuracy comparable to the accepted standard of destructive removal. Estimation or measurement of height is commonly employed to create a relationship between height and mass. This study examined several types of ground-based mobile sensing strategies for forage biomass estimation. Forage production experiments consisting of alfalfa (Medicago sativa L.), bermudagrass [Cynodon dactylon (L.) Pers.], and wheat (Triticum aestivum L.) were employed to examine sensor biomass estimation (laser, ultrasonic, and spectral) as compared to physical measurements (plate meter and meter stick) and the traditional harvest method (clipping). Predictive models were constructed via partial least squares regression and modeled estimates were compared to the physically measured biomass. Least significant difference separated mean estimates were examined to evaluate differences in the physical measurements and sensor estimates for canopy height and biomass. Differences between methods were minimal (average percent error of 11.2% for difference between predicted values versus machine and quadrat harvested biomass values (1.64 and 4.91 t·ha-1, respectively), except at the lowest measured biomass (average percent error of 89% for harvester and quad harvested biomass < 0.79 t·ha-1) and greatest measured biomass (average percent error of 18% for harvester and quad harvested biomass >6.4 t·ha-1). These data suggest that using mobile sensor-based biomass estimation models could be an effective alternative to the traditional clipping method for rapid, accurate in-field biomass estimation. [ABSTRACT FROM AUTHOR]

Polycyclic aromatic hydrocarbons (PAHs) are widespread pollutants and can negatively affect plants. Fluorene is a prevalent PAH in the contaminated environment. In this study, the effects of higher concentrations of fluorene in soil on rate of seed germination, growth, and the physiological parameters of wheat, sunflower, and alfalfa were studied. The results showed that the higher concentration of fluorene decreased rate of seed germination and seedlings growth of plants. Wheat showed the highest resistance at seed germination and seedlings growth phases, and sunflower was the most sensitive species at both stages. Therefore, it was concluded that higher resistance at seed germination could be followed by the higher resistance of seedlings. Fluorene toxicity also induced oxidative stress in plants as shown by MDA accumulation in the plants. There was a significant correlation between the lower activity of CAT and MDA accumulation in the studied plants. Therefore, CAT could be an important enzyme involved in detoxification of ROS and plants resistance to fluorene toxicity. Depending on plant species and fluorene concentration, photosynthetic pigments content was differently affected. [ABSTRACT FROM AUTHOR]

Agricultural production systems in New Mexico (NM) are under increased pressure due to climate change, drought, increased temperature, and variable precipitation, which can affect crop yields, feeds, and livestock grazing. Developing more sustainable production systems requires long-term measurements and assessment of climate change impacts on yields, especially over such a vulnerable region. Providing accurate yield predictions plays a key role in addressing a critical sustainability gap. The goal of this study is the development of effective crop yield predictions to allow for a better-informed cropland management and future production potential, and to develop climate-smart adaptation strategies for increased food security. The objectives were to (1) identify the most important climate variables that significantly influence and can be used to effectively predict yield, (2) evaluate the advantage of using remotely sensed data alone and in combination with climate variables for yield prediction, and (3) determine the significance of using short compared to long historical data records for yield prediction. This study focused on yield prediction for corn, sorghum, alfalfa, and wheat using climate and remotely sensed data for the 1920–2019 period. The results indicated that the use of normalized difference vegetation index (NDVI) alone is less accurate in predicting crop yields. The combination of climate and NDVI variables provided better predictions compared to the use of NDVI only to predict wheat, sorghum, and corn yields. However, the use of a climate only model performed better in predicting alfalfa yield. Yield predictions can be more accurate with the use of shorter data periods that are based on region-specific trends. The identification of the most important climate variables and accurate yield prediction pertaining to New Mexico's agricultural systems can aid the state in developing climate change mitigation and adaptation strategies to enhance the sustainability of these systems. [ABSTRACT FROM AUTHOR]

The leaf area index (LAI) is a key biophysical variable for agroecosystem monitoring, as well as a relevant state variable in crop modelling. For this reason, temporal and spatial determination of LAI are required to improve the understanding of several land surface processes related to vegetation dynamics and crop growth. Despite the large number of retrieved LAI products and the efforts to develop new and updated algorithms for LAI estimation, the available products are not yet capable of capturing site-specific variability, as requested in many agricultural applications. The objective of this study was to evaluate the potential of non-parametric approaches for multi-temporal LAI retrieval by Sentinel-2 multispectral data, in comparison with a VI-based parametric approach. For this purpose, we built a large database combining a multispectral satellite data set and ground LAI measurements collected over two growing seasons (2018 and 2019), including three crops (i.e., winter wheat, maize, and alfalfa) characterized by different growing cycles and canopy structures, and considering different agronomic conditions (i.e., at three farms in three different sites). The accuracy of parametric and non-parametric methods for LAI estimation was assessed by cross-validation (CV) at both the pixel and field levels over mixed-crop (MC) and crop-specific (CS) data sets. Overall, the non-parametric approach showed a higher accuracy of prediction at pixel level than parametric methods, and it was also observed that Gaussian Process Regression (GPR) did not provide any significant difference (p-value > 0.05) between the predicted values of LAI in the MC and CS data sets, regardless of the crop. Indeed, GPR at the field level showed a cross-validated coefficient of determination (R2CV) higher than 0.80 for all three crops. [ABSTRACT FROM AUTHOR]

• Feeding wheat with nitrate, fat or 3-nitrooxypropanol (3-NOP) decreased methane production. • There was no interaction between grain and nitrate, fat or 3-NOP on methane production. • Feeding wheat with nitrate, fat or 3-NOP may be effective methane mitigation strategies. Enteric methane emitted by ruminants is a nutritional inefficiency that contributes to global warming. Feeding substantial quantities of wheat grain to dairy cows has been reported to decrease enteric methane emissions compared with other feeds. Feeding methane mitigating agents such as nitrate, fat and 3-nitrooxypropanol (3-NOP) to ruminants have also been reported to decrease enteric methane emissions. This research involved three in vitro experiments that examined the combined effect of wheat grain with nitrate, fat or 3-NOP on in vitro methane mitigation. In each of the experiments, wheat grain or corn grain were incubated in combination with one of the three methane mitigating agents (nitrate, fat or 3-NOP). The fermentation of wheat grain produced 22% less methane than the fermentation of corn grain. All three methane mitigating agents decreased in vitro methane production and methane production expressed per gram of dry matter degraded. The addition of nitrate, fat and 3-NOP decreased in vitro methane production by 21, 19 and 44% respectively. The methane mitigating effect of wheat grain in combination with nitrate, fat or 3-NOP was greater than the individual effects of wheat grain, nitrate, fat or 3-NOP. The feeding of the combination of wheat grain with nitrate, fat or 3-NOP to ruminants may be effective strategies for decreasing their enteric methane emissions. [ABSTRACT FROM AUTHOR]

Based on remotely sensed imagery and socioeconomic data, this research analyzes the reasons why farmers choose one crop over another in the Bekaa Valley in Lebanon. This study mapped the area of the cultivated crop in 2017 with Sentinel-2 images. An accurate and new method was developed to extract the field boundaries from the evolution of the normalized difference vegetation index (NDVI) profile throughout the season. We collected 386 GPS locations for fields that are used for crop cultivation, from which the NDVI profile was extracted. The 386 reference fields were separated into two groups: reference locations and test locations. The Euclidean distance (ED) was calculated between these two groups, and the classification was strongly correlated to the known crop type in the field (overall accuracy: 90%). Our study area cultivated wheat (32%), spring potatoes (25%), spring vegetables (27%), orchards (11%), vineyards (7%), and alfalfa (<1%). Socioeconomic surveys showed that farmers favored these crops over others on account of their profitability. Nonetheless, the surveys highlighted a paradox: despite the lack of a political frame for agriculture in Lebanon, farmers' crop choices strongly depend on a few existing policies. [ABSTRACT FROM AUTHOR]